Operations Analytics with Machine Learning
Course project · May – October 2024
Through coursework and independent practice, I used R and Python to study operations-management topics with machine learning — model selection and evaluation, regression and prediction, classification and clustering, dimensionality reduction and evaluation metrics.
Predicting stock price movements on the STAR Market
Using historical price data from China’s STAR Market, I reduced features with principal component analysis (PCA), then predicted future price movements with logistic regression, SVM, and random forest — and compared the performance of the three approaches.
What drives video game ratings
Starting from a Kaggle dataset, I applied text analysis to identify the factors that significantly affect video game ratings, built neural-network prediction models on top of those factors, and used clustering to build user-segment profiles.